Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm

Author

Mehrkanoon, Saeid ; Moghavvemi, Mahmoud ; Fariborzi, Hossein

Author_Institution

Dept. of Electr. Eng., Univ. Malaya, Kuala Lumpur

fYear

2007

fDate

25-28 Nov. 2007

Firstpage

1245

Lastpage

1250

Abstract

The EEG signal is most useful for clinical diagnosis and in biomedical research. ElectroOculoGram (EOG), ElectroMyoGram (EMG) artifact are produced by eye movement and facial muscle movement respectively. An adaptive filtering method is proposed to remove these artifacts signals from EEG signals. Proposed method uses horizontal EOG (HEOG), vertical EOG (VEOG), and EMG signals as three reference digital filter inputs. The real-time artifact removal is implemented by multi-channel Least Mean Square algorithm. The resulting EEG signals display an accurate and artifact free feature.

Keywords

electro-oculography; electroencephalography; least mean squares methods; medical signal processing; EEG signal; LMS adaptive algorithm; adaptive filtering method; electromyogram artifact; electroocculagram; facial muscle artifact removal; horizontal EOG; multichannel least mean square algorithm; ocular artifact removal; vertical EOG; Adaptive algorithm; Adaptive filters; Clinical diagnosis; Digital filters; Electroencephalography; Electromyography; Electrooculography; Facial muscles; Least mean square algorithms; Least squares approximation; EEG; EMG; EOG; Finite Impulse Response; Least Mean Square; noise cancellation; real-time -adaptive filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-1355-3

Electronic_ISBN

978-1-4244-1356-0

Type

conf

DOI

10.1109/ICIAS.2007.4658583

Filename

4658583